𝗛𝗮𝘃𝗲 𝗪𝗲 𝗟𝗼𝘀𝘁 𝘁𝗵𝗲 𝗔𝗿𝘁 𝗼𝗳 𝗣𝘂𝗿𝗲 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻?
Early engineers worked with tiny limits. The Apollo Guidance Computer had only 2KB of RAM. Every bit mattered. Every CPU cycle was vital.
Today, we have gigabytes of memory. We often solve problems by adding more hardware. If code is slow or heavy, we add more RAM. This habit makes us lose the skill of pure optimization.
You can write better software by thinking about constraints.
Look at how you process a large text file in Python.
The common way: Many developers read an entire file into memory at once.
- You use f.readlines().
- This loads every line into a list in your RAM.
- If your file is 10GB, you need 10GB of RAM.
- This approach fails on small servers or limited devices.
The optimized way: Process the file one line at a time.
- You iterate directly over the file object.
- Python reads one line, processes it, and moves to the next.
- Your memory usage stays low and constant.
- It does not matter if the file is 1MB or 100GB.
The difference is about engineering philosophy.
Adding more resources is a temporary fix. It creates fragile software. Using constraints to drive your design creates robust software.
Optimization is not just about speed. It is about being mindful of your resources.
When you write code, ask yourself:
- How much memory does this use?
- Will this work if the data grows ten times larger?
- Am I relying on expensive hardware to hide bad code?
Better software comes from discipline.
Source: https://dev.to/prabashanadev/have-we-lost-the-art-of-pure-optimization-31b9